Chromagram


The first chromagram reveals a dynamically structured piece that doesn’t settle on a single tonal center but rather employs a wide array of pitch classes throughout its duration

Chroma-based and Timbre-based Self-similarity Matrices


Chroma-based Self-Similarity Matrix

The block-like structures and distinct lines are more apparent, indicating sections of the track where harmonic repetition homogeneity occurs:

Timbre-based Self-Similarity Matrix

The block-like structures are less clear. Instead, the streaks are more blurred and evenly distributed, suggesting that there is variability in timbre throughout the track

Music in Advertising Videos and The Study about Vietnamese music

A study by two researchers from Hungary, Monica Coronel and Anna Irimiás, confirms that music plays an essential supporting role in “destination promotional videos” and “tourism marketing,” stimulating both cognitive and affective responses. Specifically, their research reveals that background music can capture attention, reflect a destination’s characteristics, target specific audiences, highlight cultural identity, elicit emotions, and create ambience.

These findings about the importance of music in tourism marketing led me to explore Vietnamese advertising music and compare it with global music trends. In particular, my research question focuses on:

“How does the musical style of Vietnamese advertising music compare to other music? Does it have distinct characteristics, or does it align with broader global trends?”

To represent Vietnamese advertising music, I selected two tracks suitable for advertising videos showcasing Vietnamese culture and nature. After experimenting with generative AI tools, I opted for royalty-free tracks from Pixabay and SoundCloud. I used keywords such as “Vietnam,” “folk instruments,” “adventurous music,” and “travel” on both platforms, and filtered for “bright” mood and “cinematic music” theme on Pixabay. I chose these tracks because they feature Vietnamese folk instruments—a key focus—and include a strong bass that enhances engagement and evokes emotions in listeners, aligning well with the commercial and storytelling purposes of advertising videos.

Overview of Class Corpus and Lesley’s Track


This interactive boxplot presents the distribution of various Essentia features extracted from the class corpus. The black points represent all tracks in the dataset, while my tracks are highlighted in pink for better visibility.

My tracks are scattered across different features, showing varying degrees of similarity and uniqueness compared to the “average” track in the corpus:

Key Takeaways

Based on the distribution of my tracks compared to the class corpus, the key insights are:

This visualization provides a clear comparison of how my tracks align with the broader dataset and which features distinguish them. It confirms that Essentia effectively identifies track characteristics and highlights both similarities and unique elements of my track.